A “virtual machine” or a “VM” refers to a specific software-based implementation of a machine in a virtualization environment, in which the hardware resources of a real computer (e.g., CPU, memory, etc.) are virtualized or transformed into the underlying support for the fully functional virtual machine that can run its own operating system and applications on the underlying physical resources just like a real computer.
Virtualization works by inserting a thin layer of software directly on the computer hardware or on a host operating system. This layer of software contains a virtual machine monitor or “hypervisor” that allocates hardware resources dynamically and transparently. Multiple operating systems run concurrently on a single physical computer and share hardware resources with each other. By encapsulating an entire machine, including CPU, memory, operating system, and network devices, a virtual machine is completely compatible with most standard operating systems, applications, and device drivers. Most modern implementations allow several operating systems and applications to safely run at the same time on a single computer, with each having access to the resources it needs when it needs them.
Virtualization allows multiple virtual machines to run on a single physical machine, with each virtual machine sharing the resources of that one physical computer across multiple environments. Different virtual machines can run different operating systems and multiple applications on the same physical computer.
One reason for the broad adoption of virtualization in modern business and computing environments is because of the resource utilization advantages provided by virtual machines. Without virtualization, if a physical machine is limited to a single dedicated operating system, then during periods of inactivity by the dedicated operating system the physical machine is not utilized to perform useful work. This is wasteful and inefficient if there are users on other physical machines which are currently waiting for computing resources. To address this problem, virtualization allows multiple VMs to share the underlying physical resources so that during periods of inactivity by one VM, other VMs can take advantage of the resource availability to process workloads. This can produce great efficiencies for the utilization of physical devices, and can result in reduced redundancies and better resource cost management.
Many organizations use data centers to implement virtualization, where the data centers are typically architected with traditional servers that communicate with a set of networked storage devices over a network. For example, many data centers are designed using diskless computers (“application servers”) that communicate with a set of networked storage appliances (“storage servers”) via a network, such as a Fiber Channel or Ethernet network.
The problem is that this traditional approach cannot adapt to the modern demands of virtualization, which is particularly problematic with respect to the way these traditional architectures manage storage. One reason for this is because the traditional network storage-based architecture is designed for physical servers that serve relatively static workloads, but which is not flexible or adaptable enough to adequately handle the dynamic nature of storage and virtual machines that, in a virtualization or cloud computing environment, may be created or moved on the fly from one network location to another.
Moreover, the traditional approach relies upon very large and specialized rackmount or freestanding compute and storage devices that are managed by a central storage manager. This approach does not scale very well, since the central storage manager becomes a very significant performance bottleneck as the number of storage devices increase. Moreover, the traditional compute and storage devices are expensive to purchase, maintain, and power, and are large enough to require a significant investment just in terms of the amount of physical space that is needed to implement the data center.
Given these challenges with the traditional data center architectures, it has become clear that the conventional approaches to implement a data center for virtualization presents excessive levels of cost and complexity, while being very ill-adapted to the needs of modern virtualization systems. These problems are further exacerbated by the fact that data volumes are constantly growing at a rapid pace in the modern data center, thanks to the ease of creating new VMs. In the enterprise, new initiatives like desktop virtualization contribute to this trend of increased data volumes. This growing pool of VMs is exerting tremendous cost, performance and manageability pressure on the traditional architecture that connects compute to storage over a multi-hop network.
Therefore, there is a need for an improved approach to implement an architecture for a virtualization data center.